Josh Dillon, Last Revised January 2022
This notebook examines an individual antenna's performance over a whole season. This notebook parses information from each nightly rtp_summarynotebook (as saved to .csvs) and builds a table describing antenna performance. It also reproduces per-antenna plots from each auto_metrics notebook pertinent to the specific antenna.
import os
from IPython.display import display, HTML
display(HTML("<style>.container { width:100% !important; }</style>"))
# If you want to run this notebook locally, copy the output of the next cell into the next line of this cell.
# antenna = "004"
# csv_folder = '/lustre/aoc/projects/hera/H5C/H5C_Notebooks/_rtp_summary_'
# auto_metrics_folder = '/lustre/aoc/projects/hera/H5C/H5C_Notebooks/auto_metrics_inspect'
# os.environ["ANTENNA"] = antenna
# os.environ["CSV_FOLDER"] = csv_folder
# os.environ["AUTO_METRICS_FOLDER"] = auto_metrics_folder
# Use environment variables to figure out path to the csvs and auto_metrics
antenna = str(int(os.environ["ANTENNA"]))
csv_folder = os.environ["CSV_FOLDER"]
auto_metrics_folder = os.environ["AUTO_METRICS_FOLDER"]
print(f'antenna = "{antenna}"')
print(f'csv_folder = "{csv_folder}"')
print(f'auto_metrics_folder = "{auto_metrics_folder}"')
antenna = "93" csv_folder = "/home/obs/src/H6C_Notebooks/_rtp_summary_" auto_metrics_folder = "/home/obs/src/H6C_Notebooks/auto_metrics_inspect"
display(HTML(f'<h1 style=font-size:50px><u>Antenna {antenna} Report</u><p></p></h1>'))
import numpy as np
import pandas as pd
pd.set_option('display.max_rows', 1000)
import glob
import re
from hera_notebook_templates.utils import status_colors, Antenna
# load csvs and auto_metrics htmls in reverse chronological order
csvs = sorted(glob.glob(os.path.join(csv_folder, 'rtp_summary_table*.csv')))[::-1]
print(f'Found {len(csvs)} csvs in {csv_folder}')
auto_metric_htmls = sorted(glob.glob(auto_metrics_folder + '/auto_metrics_inspect_*.html'))[::-1]
print(f'Found {len(auto_metric_htmls)} auto_metrics notebooks in {auto_metrics_folder}')
Found 47 csvs in /home/obs/src/H6C_Notebooks/_rtp_summary_ Found 45 auto_metrics notebooks in /home/obs/src/H6C_Notebooks/auto_metrics_inspect
# Per-season options
mean_round_modz_cut = 4
dead_cut = 0.4
crossed_cut = 0.0
def jd_to_summary_url(jd):
return f'https://htmlpreview.github.io/?https://github.com/HERA-Team/H6C_Notebooks/blob/main/_rtp_summary_/rtp_summary_{jd}.html'
def jd_to_auto_metrics_url(jd):
return f'https://htmlpreview.github.io/?https://github.com/HERA-Team/H6C_Notebooks/blob/main/auto_metrics_inspect/auto_metrics_inspect_{jd}.html'
this_antenna = None
jds = []
# parse information about antennas and nodes
for csv in csvs:
df = pd.read_csv(csv)
for n in range(len(df)):
# Add this day to the antenna
row = df.loc[n]
if isinstance(row['Ant'], str) and '<a href' in row['Ant']:
antnum = int(row['Ant'].split('</a>')[0].split('>')[-1]) # it's a link, extract antnum
else:
antnum = int(row['Ant'])
if antnum != int(antenna):
continue
if np.issubdtype(type(row['Node']), np.integer):
row['Node'] = str(row['Node'])
if type(row['Node']) == str and row['Node'].isnumeric():
row['Node'] = 'N' + ('0' if len(row['Node']) == 1 else '') + row['Node']
if this_antenna is None:
this_antenna = Antenna(row['Ant'], row['Node'])
jd = [int(s) for s in re.split('_|\.', csv) if s.isdigit()][-1]
jds.append(jd)
this_antenna.add_day(jd, row)
break
# build dataframe
to_show = {'JDs': [f'<a href="{jd_to_summary_url(jd)}" target="_blank">{jd}</a>' for jd in jds]}
to_show['A Priori Status'] = [this_antenna.statuses[jd] for jd in jds]
df = pd.DataFrame(to_show)
# create bar chart columns for flagging percentages:
bar_cols = {}
bar_cols['Auto Metrics Flags'] = [this_antenna.auto_flags[jd] for jd in jds]
bar_cols[f'Dead Fraction in Ant Metrics (Jee)'] = [this_antenna.dead_flags_Jee[jd] for jd in jds]
bar_cols[f'Dead Fraction in Ant Metrics (Jnn)'] = [this_antenna.dead_flags_Jnn[jd] for jd in jds]
bar_cols['Crossed Fraction in Ant Metrics'] = [this_antenna.crossed_flags[jd] for jd in jds]
bar_cols['Flag Fraction Before Redcal'] = [this_antenna.flags_before_redcal[jd] for jd in jds]
bar_cols['Flagged By Redcal chi^2 Fraction'] = [this_antenna.redcal_flags[jd] for jd in jds]
for col in bar_cols:
df[col] = bar_cols[col]
z_score_cols = {}
z_score_cols['ee Shape Modified Z-Score'] = [this_antenna.ee_shape_zs[jd] for jd in jds]
z_score_cols['nn Shape Modified Z-Score'] = [this_antenna.nn_shape_zs[jd] for jd in jds]
z_score_cols['ee Power Modified Z-Score'] = [this_antenna.ee_power_zs[jd] for jd in jds]
z_score_cols['nn Power Modified Z-Score'] = [this_antenna.nn_power_zs[jd] for jd in jds]
z_score_cols['ee Temporal Variability Modified Z-Score'] = [this_antenna.ee_temp_var_zs[jd] for jd in jds]
z_score_cols['nn Temporal Variability Modified Z-Score'] = [this_antenna.nn_temp_var_zs[jd] for jd in jds]
z_score_cols['ee Temporal Discontinuties Modified Z-Score'] = [this_antenna.ee_temp_discon_zs[jd] for jd in jds]
z_score_cols['nn Temporal Discontinuties Modified Z-Score'] = [this_antenna.nn_temp_discon_zs[jd] for jd in jds]
for col in z_score_cols:
df[col] = z_score_cols[col]
ant_metrics_cols = {}
ant_metrics_cols['Average Dead Ant Metric (Jee)'] = [this_antenna.Jee_dead_metrics[jd] for jd in jds]
ant_metrics_cols['Average Dead Ant Metric (Jnn)'] = [this_antenna.Jnn_dead_metrics[jd] for jd in jds]
ant_metrics_cols['Average Crossed Ant Metric'] = [this_antenna.crossed_metrics[jd] for jd in jds]
for col in ant_metrics_cols:
df[col] = ant_metrics_cols[col]
redcal_cols = {}
redcal_cols['Median chi^2 Per Antenna (Jee)'] = [this_antenna.Jee_chisqs[jd] for jd in jds]
redcal_cols['Median chi^2 Per Antenna (Jnn)'] = [this_antenna.Jnn_chisqs[jd] for jd in jds]
for col in redcal_cols:
df[col] = redcal_cols[col]
# style dataframe
table = df.style.hide_index()\
.applymap(lambda val: f'background-color: {status_colors[val]}' if val in status_colors else '', subset=['A Priori Status']) \
.background_gradient(cmap='viridis', vmax=mean_round_modz_cut * 3, vmin=0, axis=None, subset=list(z_score_cols.keys())) \
.background_gradient(cmap='bwr_r', vmin=dead_cut-.25, vmax=dead_cut+.25, axis=0, subset=list([col for col in ant_metrics_cols if 'dead' in col.lower()])) \
.background_gradient(cmap='bwr_r', vmin=crossed_cut-.25, vmax=crossed_cut+.25, axis=0, subset=list([col for col in ant_metrics_cols if 'crossed' in col.lower()])) \
.background_gradient(cmap='plasma', vmax=4, vmin=1, axis=None, subset=list(redcal_cols.keys())) \
.applymap(lambda val: 'font-weight: bold' if val < dead_cut else '', subset=list([col for col in ant_metrics_cols if 'dead' in col.lower()])) \
.applymap(lambda val: 'font-weight: bold' if val < crossed_cut else '', subset=list([col for col in ant_metrics_cols if 'crossed' in col.lower()])) \
.applymap(lambda val: 'font-weight: bold' if val > mean_round_modz_cut else '', subset=list(z_score_cols.keys())) \
.applymap(lambda val: 'color: red' if val > mean_round_modz_cut else '', subset=list(z_score_cols.keys())) \
.bar(subset=list(bar_cols.keys()), vmin=0, vmax=1) \
.format({col: '{:,.4f}'.format for col in z_score_cols}) \
.format({col: '{:,.4f}'.format for col in ant_metrics_cols}) \
.format('{:,.2%}', na_rep='-', subset=list(bar_cols.keys())) \
.set_table_styles([dict(selector="th",props=[('max-width', f'70pt')])])
This table reproduces each night's row for this antenna from the RTP Summary notebooks. For more info on the columns, see those notebooks, linked in the JD column.
display(HTML(f'<h2>Antenna {antenna}, Node {this_antenna.node}:</h2>'))
HTML(table.render(render_links=True, escape=False))
| JDs | A Priori Status | Auto Metrics Flags | Dead Fraction in Ant Metrics (Jee) | Dead Fraction in Ant Metrics (Jnn) | Crossed Fraction in Ant Metrics | Flag Fraction Before Redcal | Flagged By Redcal chi^2 Fraction | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | Average Dead Ant Metric (Jee) | Average Dead Ant Metric (Jnn) | Average Crossed Ant Metric | Median chi^2 Per Antenna (Jee) | Median chi^2 Per Antenna (Jnn) |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 2459862 | digital_ok | 0.00% | 0.00% | 0.00% | 0.00% | - | - | 1.554845 | 0.446460 | 2.674076 | 0.528490 | 1.782683 | -0.472000 | 2.976159 | -0.751770 | 0.6816 | 0.7042 | 0.4183 | nan | nan |
| 2459861 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | - | - | 0.949341 | 0.324292 | 1.059260 | 0.771718 | 1.830576 | 0.129454 | 8.221129 | -0.659485 | 0.7067 | 0.6868 | 0.4162 | nan | nan |
| 2459860 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | - | - | 1.021302 | -0.009111 | 0.505296 | -0.926769 | 3.303974 | -0.191653 | 4.684052 | -0.856326 | 0.7139 | 0.6860 | 0.4110 | nan | nan |
| 2459859 | digital_ok | 0.00% | 0.00% | 0.00% | 0.00% | - | - | 0.672849 | 0.151591 | 1.273873 | 0.673734 | 0.776319 | -0.181467 | 2.457797 | -0.616013 | 0.7164 | 0.6891 | 0.4081 | nan | nan |
| 2459858 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | 100.00% | 0.00% | 0.913631 | 0.190644 | 1.216201 | 0.636181 | 3.441761 | -0.290103 | 6.302143 | -0.631934 | 0.7265 | 0.6935 | 0.4175 | 3.318778 | 2.668871 |
| 2459857 | digital_ok | 100.00% | 100.00% | 100.00% | 0.00% | - | - | -0.443031 | 0.351364 | 0.214835 | 0.125087 | 8.448254 | 2.125437 | 10.460070 | 2.761883 | 0.0251 | 0.0245 | 0.0005 | nan | nan |
| 2459856 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | 100.00% | 0.00% | 1.955779 | 0.464986 | 2.543888 | -0.327343 | 2.009958 | -0.581472 | 5.670784 | -0.888447 | 0.7191 | 0.7100 | 0.4024 | 3.135458 | 2.788829 |
| 2459855 | digital_ok | 100.00% | 100.00% | 100.00% | 0.00% | 100.00% | 0.00% | 75.200737 | 75.375280 | inf | inf | 4347.863424 | 4353.794572 | 4168.874277 | 4166.418551 | 0.0094 | 0.0096 | 0.0011 | 0.000000 | 0.000000 |
| 2459854 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | 100.00% | 0.00% | 2.357021 | 0.288317 | 1.300499 | -0.737980 | 2.425534 | 0.071041 | 9.579551 | 0.784636 | 0.7228 | 0.7481 | 0.4343 | 3.163804 | 2.856925 |
| 2459853 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | 100.00% | 0.00% | 1.211674 | 0.038487 | 1.343669 | -0.830007 | 2.272249 | -0.465223 | 8.083988 | -0.499965 | 0.7398 | 0.6951 | 0.4249 | 3.395199 | 3.029207 |
| 2459852 | digital_ok | 0.00% | 0.00% | 0.00% | 0.00% | 8.65% | 0.00% | 1.190657 | 1.976192 | -0.228007 | 0.193004 | 1.473699 | -0.350319 | -0.205196 | -0.348270 | 0.8390 | 0.8441 | 0.2389 | 3.008886 | 2.788400 |
| 2459851 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | 100.00% | 0.00% | 1.394765 | 0.648860 | 0.842720 | -0.582904 | 4.168338 | 1.179269 | 6.207925 | -0.026572 | 0.7605 | 0.7522 | 0.3368 | 4.185170 | 3.318546 |
| 2459850 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | 100.00% | 0.00% | 1.392626 | 0.325963 | 0.859979 | -0.697097 | 1.539285 | -0.358142 | 11.011520 | -0.389818 | 0.7460 | 0.7626 | 0.3534 | 3.295855 | 2.969490 |
| 2459849 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | 100.00% | 0.00% | 2.097658 | 0.322528 | 2.953570 | -0.614623 | 4.043603 | -0.445715 | 8.681984 | -0.711724 | 0.7428 | 0.7560 | 0.3585 | 3.874935 | 3.420981 |
| 2459848 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | 100.00% | 0.00% | 2.222049 | 1.245096 | 10.391813 | 0.982380 | 1.794016 | -0.296483 | 4.159945 | -0.830649 | 0.7008 | 0.7542 | 0.3850 | 3.034265 | 3.061444 |
| 2459847 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | 100.00% | 0.00% | 2.516951 | 1.342262 | 9.109467 | 1.090908 | 3.763374 | -0.089631 | 3.772786 | -0.906385 | 0.7005 | 0.6865 | 0.4339 | 3.169889 | 2.900511 |
| 2459845 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | 100.00% | 0.00% | 3.039962 | 1.902155 | 14.444302 | 0.661214 | 1.895965 | -0.128212 | 3.254506 | -1.281809 | 0.7306 | 0.7553 | 0.3642 | 0.000000 | 0.000000 |
| 2459844 | digital_ok | 100.00% | 100.00% | 100.00% | 0.00% | - | - | 5.985727 | -0.689512 | 1.819477 | 0.835388 | 3.551836 | 0.784094 | 4.971758 | 1.206518 | 0.0245 | 0.0242 | 0.0005 | nan | nan |
| 2459843 | digital_ok | 100.00% | 8.84% | 0.66% | 0.00% | 100.00% | 0.00% | 11.408784 | 0.455039 | 16.449688 | -1.078724 | 47.134420 | -0.606504 | 0.180666 | -0.875078 | 0.5491 | 0.7532 | 0.4387 | 2.460802 | 4.847519 |
| 2459842 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | 100.00% | 0.00% | 5.917801 | -0.395288 | 7.612688 | 0.292085 | -1.517563 | 1.132634 | 0.250288 | -0.007162 | 0.5601 | 0.6863 | 0.2899 | 2.269995 | 3.780639 |
| 2459841 | digital_ok | 100.00% | 100.00% | 100.00% | 0.00% | - | - | 12.892162 | 2.343546 | 3.465001 | -0.446526 | 0.979482 | -0.283683 | 2.208889 | 1.993814 | 0.0240 | 0.0241 | 0.0005 | nan | nan |
| 2459840 | digital_ok | 0.00% | 100.00% | 100.00% | 0.00% | - | - | -1.488385 | -0.895806 | -0.431976 | 0.175047 | -0.437239 | 0.169686 | 0.187106 | 2.081512 | 0.0234 | 0.0228 | 0.0008 | nan | nan |
| 2459839 | digital_ok | 100.00% | - | - | - | - | - | -1.252381 | 0.221073 | -1.021708 | 0.517625 | 1.373179 | 6.391618 | 1.006933 | 3.142716 | nan | nan | nan | nan | nan |
| 2459838 | digital_ok | 100.00% | 100.00% | 100.00% | 0.00% | 100.00% | 0.00% | 314.443728 | 313.289612 | inf | inf | 13290.835836 | 13349.603819 | 9227.577134 | 9274.722921 | nan | nan | nan | 0.000000 | 0.000000 |
| 2459836 | digital_ok | - | 100.00% | 100.00% | 0.00% | - | - | nan | nan | nan | nan | nan | nan | nan | nan | 0.0376 | 0.0358 | 0.0047 | nan | nan |
| 2459835 | digital_ok | 100.00% | 100.00% | 100.00% | 0.00% | - | - | nan | nan | inf | inf | nan | nan | nan | nan | nan | nan | nan | nan | nan |
| 2459833 | digital_ok | 0.00% | 100.00% | 100.00% | 0.00% | - | - | -0.716397 | 1.562774 | -0.214599 | -0.648501 | 3.855061 | 1.715639 | 1.712522 | -0.013175 | 0.0300 | 0.0323 | 0.0022 | nan | nan |
| 2459832 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | 100.00% | 0.00% | -0.020084 | -0.352777 | 1.853802 | -0.268932 | 6.179042 | -0.376405 | 4.603769 | -0.924084 | 0.7426 | 0.4449 | 0.5628 | 3.418403 | 2.873161 |
| 2459831 | digital_ok | 0.00% | 100.00% | 100.00% | 0.00% | - | - | -1.082742 | 0.713627 | -1.281409 | 0.601126 | 0.702185 | -0.076170 | 0.036486 | 1.454221 | 0.0307 | 0.0359 | 0.0027 | nan | nan |
| 2459830 | digital_ok | 100.00% | 0.00% | 16.13% | 0.00% | 100.00% | 0.00% | 0.247655 | -0.358326 | 3.385973 | 0.165170 | 4.665621 | -0.917454 | 4.289555 | -1.216791 | 0.7371 | 0.4365 | 0.5513 | 4.861743 | 4.095833 |
| 2459829 | digital_ok | 100.00% | 0.00% | 0.54% | 0.00% | 100.00% | 0.00% | 0.549366 | -0.232742 | 4.066331 | 0.296638 | 2.754107 | -0.851814 | 6.479326 | -0.576738 | 0.6632 | 0.5767 | 0.4141 | 5.126944 | 4.715735 |
| 2459828 | digital_ok | 0.00% | 0.00% | 0.00% | 0.00% | 0.00% | 0.00% | 0.807572 | -0.221173 | 3.498930 | 0.099164 | 3.200447 | -0.044212 | 1.979028 | -1.684118 | 0.7315 | 0.4550 | 0.5291 | 2.003902 | 1.656355 |
| 2459827 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | 100.00% | 0.00% | -0.057656 | 0.072820 | 4.471351 | 0.955482 | 1.000049 | -0.732839 | 0.033890 | -1.114495 | 0.6731 | 0.5856 | 0.4125 | 7.342098 | 6.333634 |
| 2459826 | digital_ok | 100.00% | 16.13% | 16.13% | 0.00% | 100.00% | 0.00% | 0.614934 | -0.136545 | 3.672744 | 0.931988 | 3.999640 | -0.473538 | 2.622787 | -0.977836 | 0.6568 | 0.4262 | 0.4560 | 6.440174 | 7.233009 |
| 2459825 | digital_ok | 0.00% | 100.00% | 100.00% | 0.00% | 100.00% | 0.00% | 0.708252 | 0.400738 | 2.616065 | -0.304592 | 1.754650 | -0.535474 | -0.468658 | -0.685688 | 0.0762 | 0.0952 | 0.0143 | 0.000000 | 0.000000 |
| 2459824 | digital_ok | 0.00% | 100.00% | 100.00% | 0.00% | 100.00% | 0.00% | 0.101204 | 1.264823 | 2.321363 | -0.184329 | 1.272098 | -1.057768 | 2.027073 | -0.836079 | 0.0677 | 0.0833 | 0.0081 | 0.000000 | 0.000000 |
| 2459823 | digital_ok | 0.00% | 100.00% | 100.00% | 0.00% | 100.00% | 0.00% | 0.975470 | -0.419479 | 2.775158 | 0.801997 | 1.456204 | -0.634084 | 0.778937 | -1.558880 | 0.0711 | 0.0823 | 0.0113 | 0.000000 | 0.000000 |
| 2459822 | digital_ok | 100.00% | 100.00% | 100.00% | 0.00% | 100.00% | 0.00% | 1.573453 | 0.532475 | 4.059735 | 0.584369 | 4.069221 | -0.879414 | 0.079832 | -0.684840 | 0.0816 | 0.0914 | 0.0142 | 0.000000 | 0.000000 |
| 2459821 | digital_ok | 100.00% | 100.00% | 100.00% | 0.00% | 100.00% | 0.00% | 1.594740 | -0.361073 | 4.132051 | 0.682433 | 4.092754 | -0.353396 | 0.713703 | 0.938130 | 0.0666 | 0.0794 | 0.0110 | 56.404512 | 67.580291 |
| 2459820 | digital_ok | 100.00% | 100.00% | 100.00% | 0.00% | 100.00% | 0.00% | 0.225633 | -0.360596 | 4.490239 | 0.836838 | 7.792813 | -1.549509 | 3.443526 | -0.959281 | 0.0699 | 0.0813 | 0.0098 | 0.000000 | 0.000000 |
| 2459817 | digital_ok | 100.00% | 100.00% | 100.00% | 0.00% | 100.00% | 0.00% | 2.224763 | -1.006600 | 3.747928 | 0.449876 | 4.986603 | -0.282746 | 0.969203 | 0.413777 | 0.0759 | 0.0827 | 0.0122 | 43.781689 | 56.241643 |
| 2459816 | digital_ok | 100.00% | 100.00% | 100.00% | 0.00% | 100.00% | 0.00% | 0.608297 | -0.024967 | 3.385306 | -0.023211 | 3.962888 | -0.834550 | 4.583553 | -0.470627 | 0.0695 | 0.0884 | 0.0181 | 1.175327 | 1.170168 |
| 2459815 | digital_ok | 100.00% | 100.00% | 100.00% | 0.00% | 100.00% | 0.00% | 1.717108 | -0.907083 | 3.013896 | 0.294161 | 3.512655 | -0.770688 | 5.627091 | -0.834835 | 0.0798 | 0.0912 | 0.0117 | 0.944238 | 0.945807 |
| 2459814 | digital_ok | 0.00% | - | - | - | - | - | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan |
| 2459813 | digital_ok | 100.00% | 100.00% | 100.00% | 0.00% | 100.00% | 0.00% | 1.713469 | 9.794083 | 3.190282 | 13.691734 | 10.589393 | 40.494439 | 4.363040 | -3.419692 | 0.0945 | 0.1275 | 0.0196 | 0.000000 | 0.000000 |
auto_metrics notebooks.¶htmls_to_display = []
for am_html in auto_metric_htmls:
html_to_display = ''
# read html into a list of lines
with open(am_html) as f:
lines = f.readlines()
# find section with this antenna's metric plots and add to html_to_display
jd = [int(s) for s in re.split('_|\.', am_html) if s.isdigit()][-1]
try:
section_start_line = lines.index(f'<h2>Antenna {antenna}: {jd}</h2>\n')
except ValueError:
continue
html_to_display += lines[section_start_line].replace(str(jd), f'<a href="{jd_to_auto_metrics_url(jd)}" target="_blank">{jd}</a>')
for line in lines[section_start_line + 1:]:
html_to_display += line
if '<hr' in line:
htmls_to_display.append(html_to_display)
break
These figures are reproduced from auto_metrics notebooks. For more info on the specific plots and metrics, see those notebooks (linked at the JD). The most recent 100 days (at most) are shown.
for i, html_to_display in enumerate(htmls_to_display):
if i == 100:
break
display(HTML(html_to_display))
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 93 | N10 | digital_ok | ee Temporal Discontinuties | 2.976159 | 1.554845 | 0.446460 | 2.674076 | 0.528490 | 1.782683 | -0.472000 | 2.976159 | -0.751770 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 93 | N10 | digital_ok | ee Temporal Discontinuties | 8.221129 | 0.324292 | 0.949341 | 0.771718 | 1.059260 | 0.129454 | 1.830576 | -0.659485 | 8.221129 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 93 | N10 | digital_ok | ee Temporal Discontinuties | 4.684052 | 1.021302 | -0.009111 | 0.505296 | -0.926769 | 3.303974 | -0.191653 | 4.684052 | -0.856326 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 93 | N10 | digital_ok | ee Temporal Discontinuties | 2.457797 | 0.672849 | 0.151591 | 1.273873 | 0.673734 | 0.776319 | -0.181467 | 2.457797 | -0.616013 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 93 | N10 | digital_ok | ee Temporal Discontinuties | 6.302143 | 0.190644 | 0.913631 | 0.636181 | 1.216201 | -0.290103 | 3.441761 | -0.631934 | 6.302143 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 93 | N10 | digital_ok | ee Temporal Discontinuties | 10.460070 | 0.351364 | -0.443031 | 0.125087 | 0.214835 | 2.125437 | 8.448254 | 2.761883 | 10.460070 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 93 | N10 | digital_ok | ee Temporal Discontinuties | 5.670784 | 1.955779 | 0.464986 | 2.543888 | -0.327343 | 2.009958 | -0.581472 | 5.670784 | -0.888447 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 93 | N10 | digital_ok | nn Power | inf | 75.375280 | 75.200737 | inf | inf | 4353.794572 | 4347.863424 | 4166.418551 | 4168.874277 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 93 | N10 | digital_ok | ee Temporal Discontinuties | 9.579551 | 0.288317 | 2.357021 | -0.737980 | 1.300499 | 0.071041 | 2.425534 | 0.784636 | 9.579551 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 93 | N10 | digital_ok | ee Temporal Discontinuties | 8.083988 | 0.038487 | 1.211674 | -0.830007 | 1.343669 | -0.465223 | 2.272249 | -0.499965 | 8.083988 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 93 | N10 | digital_ok | nn Shape | 1.976192 | 1.190657 | 1.976192 | -0.228007 | 0.193004 | 1.473699 | -0.350319 | -0.205196 | -0.348270 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 93 | N10 | digital_ok | ee Temporal Discontinuties | 6.207925 | 1.394765 | 0.648860 | 0.842720 | -0.582904 | 4.168338 | 1.179269 | 6.207925 | -0.026572 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 93 | N10 | digital_ok | ee Temporal Discontinuties | 11.011520 | 1.392626 | 0.325963 | 0.859979 | -0.697097 | 1.539285 | -0.358142 | 11.011520 | -0.389818 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 93 | N10 | digital_ok | ee Temporal Discontinuties | 8.681984 | 2.097658 | 0.322528 | 2.953570 | -0.614623 | 4.043603 | -0.445715 | 8.681984 | -0.711724 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 93 | N10 | digital_ok | ee Power | 10.391813 | 1.245096 | 2.222049 | 0.982380 | 10.391813 | -0.296483 | 1.794016 | -0.830649 | 4.159945 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 93 | N10 | digital_ok | ee Power | 9.109467 | 1.342262 | 2.516951 | 1.090908 | 9.109467 | -0.089631 | 3.763374 | -0.906385 | 3.772786 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 93 | N10 | digital_ok | ee Power | 14.444302 | 1.902155 | 3.039962 | 0.661214 | 14.444302 | -0.128212 | 1.895965 | -1.281809 | 3.254506 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 93 | N10 | digital_ok | ee Shape | 5.985727 | 5.985727 | -0.689512 | 1.819477 | 0.835388 | 3.551836 | 0.784094 | 4.971758 | 1.206518 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 93 | N10 | digital_ok | ee Temporal Variability | 47.134420 | 0.455039 | 11.408784 | -1.078724 | 16.449688 | -0.606504 | 47.134420 | -0.875078 | 0.180666 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 93 | N10 | digital_ok | ee Power | 7.612688 | 5.917801 | -0.395288 | 7.612688 | 0.292085 | -1.517563 | 1.132634 | 0.250288 | -0.007162 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 93 | N10 | digital_ok | ee Shape | 12.892162 | 12.892162 | 2.343546 | 3.465001 | -0.446526 | 0.979482 | -0.283683 | 2.208889 | 1.993814 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 93 | N10 | digital_ok | nn Temporal Discontinuties | 2.081512 | -1.488385 | -0.895806 | -0.431976 | 0.175047 | -0.437239 | 0.169686 | 0.187106 | 2.081512 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 93 | N10 | digital_ok | nn Temporal Variability | 6.391618 | 0.221073 | -1.252381 | 0.517625 | -1.021708 | 6.391618 | 1.373179 | 3.142716 | 1.006933 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 93 | N10 | digital_ok | nn Power | inf | 313.289612 | 314.443728 | inf | inf | 13349.603819 | 13290.835836 | 9274.722921 | 9227.577134 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 93 | N10 | digital_ok | nn Shape | nan | nan | nan | inf | inf | nan | nan | nan | nan |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 93 | N10 | digital_ok | ee Temporal Variability | 3.855061 | 1.562774 | -0.716397 | -0.648501 | -0.214599 | 1.715639 | 3.855061 | -0.013175 | 1.712522 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 93 | N10 | digital_ok | ee Temporal Variability | 6.179042 | -0.020084 | -0.352777 | 1.853802 | -0.268932 | 6.179042 | -0.376405 | 4.603769 | -0.924084 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 93 | N10 | digital_ok | nn Temporal Discontinuties | 1.454221 | -1.082742 | 0.713627 | -1.281409 | 0.601126 | 0.702185 | -0.076170 | 0.036486 | 1.454221 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 93 | N10 | digital_ok | ee Temporal Variability | 4.665621 | 0.247655 | -0.358326 | 3.385973 | 0.165170 | 4.665621 | -0.917454 | 4.289555 | -1.216791 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 93 | N10 | digital_ok | ee Temporal Discontinuties | 6.479326 | -0.232742 | 0.549366 | 0.296638 | 4.066331 | -0.851814 | 2.754107 | -0.576738 | 6.479326 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 93 | N10 | digital_ok | ee Power | 3.498930 | -0.221173 | 0.807572 | 0.099164 | 3.498930 | -0.044212 | 3.200447 | -1.684118 | 1.979028 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 93 | N10 | digital_ok | ee Power | 4.471351 | -0.057656 | 0.072820 | 4.471351 | 0.955482 | 1.000049 | -0.732839 | 0.033890 | -1.114495 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 93 | N10 | digital_ok | ee Temporal Variability | 3.999640 | -0.136545 | 0.614934 | 0.931988 | 3.672744 | -0.473538 | 3.999640 | -0.977836 | 2.622787 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 93 | N10 | digital_ok | ee Power | 2.616065 | 0.400738 | 0.708252 | -0.304592 | 2.616065 | -0.535474 | 1.754650 | -0.685688 | -0.468658 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 93 | N10 | digital_ok | ee Power | 2.321363 | 0.101204 | 1.264823 | 2.321363 | -0.184329 | 1.272098 | -1.057768 | 2.027073 | -0.836079 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 93 | N10 | digital_ok | ee Power | 2.775158 | -0.419479 | 0.975470 | 0.801997 | 2.775158 | -0.634084 | 1.456204 | -1.558880 | 0.778937 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 93 | N10 | digital_ok | ee Temporal Variability | 4.069221 | 1.573453 | 0.532475 | 4.059735 | 0.584369 | 4.069221 | -0.879414 | 0.079832 | -0.684840 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 93 | N10 | digital_ok | ee Power | 4.132051 | -0.361073 | 1.594740 | 0.682433 | 4.132051 | -0.353396 | 4.092754 | 0.938130 | 0.713703 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 93 | N10 | digital_ok | ee Temporal Variability | 7.792813 | 0.225633 | -0.360596 | 4.490239 | 0.836838 | 7.792813 | -1.549509 | 3.443526 | -0.959281 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 93 | N10 | digital_ok | ee Temporal Variability | 4.986603 | 2.224763 | -1.006600 | 3.747928 | 0.449876 | 4.986603 | -0.282746 | 0.969203 | 0.413777 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 93 | N10 | digital_ok | ee Temporal Discontinuties | 4.583553 | -0.024967 | 0.608297 | -0.023211 | 3.385306 | -0.834550 | 3.962888 | -0.470627 | 4.583553 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 93 | N10 | digital_ok | ee Temporal Discontinuties | 5.627091 | -0.907083 | 1.717108 | 0.294161 | 3.013896 | -0.770688 | 3.512655 | -0.834835 | 5.627091 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 93 | N10 | digital_ok | nn Shape | nan | nan | nan | nan | nan | nan | nan | nan | nan |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 93 | N10 | digital_ok | nn Temporal Variability | 40.494439 | 9.794083 | 1.713469 | 13.691734 | 3.190282 | 40.494439 | 10.589393 | -3.419692 | 4.363040 |